7 citations · 18 across the 31 of their papers we have counts for
17 papers · 1 filter
VoxTubeS: Distributable Speaker-Anonymized Synthetic Speech Corpora and Their Analysis
Zhe Zhang, Yexin Lu, Junichi Yamagishi
Large speech corpora support research, but recordings can expose speaker identity because voice remains a recognizable biometric. Meanwhile, speech data derived from media can be d…
Does Fine-tuning by Reinforcement Learning Improve Generalization in Binary Speech Deepfake Detection?
Xin Wang, Ge Wanying, Junichi Yamagishi
Building speech deepfake detection models that are generalizable to unseen attacks remains a challenging problem. Although the field has shifted toward a pre-training and fine-tuni…
Human perception of audio deepfakes: the role of language and speaking style
Eugenia San Segundo, Aurora López-Jareño, Xin Wang +1
Audio deepfakes have reached a level of realism that makes it increasingly difficult to distinguish between human and artificial voices, which poses risks such as identity theft or…
FakeMark: Deepfake Speech Attribution With Watermarked Artifacts
Wanying Ge, Xin Wang, Junichi Yamagishi
Deepfake speech attribution remains challenging for existing solutions. Classifier-based solutions often fail to generalize to domain-shifted samples, and watermarking-based soluti…
Target speaker anonymization in multi-speaker recordings
Natalia Tomashenko, Junichi Yamagishi, Xin Wang +2
Most of the existing speaker anonymization research has focused on single-speaker audio, leading to the development of techniques and evaluation metrics optimized for such conditio…
Towards Data Drift Monitoring for Speech Deepfake Detection in the context of MLOps
Xin Wang, Wanying Ge, Junichi Yamagishi
When being delivered in applications or services on the cloud, static speech deepfake detectors that are not updated will become vulnerable to newly created speech deepfake attacks…
Mitigating Language Mismatch in SSL-Based Speaker Anonymization
Zhe Zhang, Wen-Chin Huang, Xin Wang +2
Speaker anonymization aims to protect speaker identity while preserving content information and the intelligibility of speech. However, most speaker anonymization systems (SASs) ar…
From Sharpness to Better Generalization for Speech Deepfake Detection
Wen Huang, Xuechen Liu, Xin Wang +2
Generalization remains a critical challenge in speech deepfake detection (SDD). While various approaches aim to improve robustness, generalization is typically assessed through per…
Post-training for Deepfake Speech Detection
Wanying Ge, Xin Wang, Xuechen Liu +1
We introduce a post-training approach that adapts self-supervised learning (SSL) models for deepfake speech detection by bridging the gap between general pre-training and domain-sp…
ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech
Xin Wang, Héctor Delgado, Hemlata Tak +26
ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake attacks as well as the design of detection solutions. We introduce…
ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale
Xin Wang, Hector Delgado, Hemlata Tak +10
ASVspoof 5 is the fifth edition in a series of challenges that promote the study of speech spoofing and deepfake attacks, and the design of detection solutions. Compared to previou…
The VoicePrivacy 2022 Challenge: Progress and Perspectives in Voice Anonymisation
Michele Panariello, Natalia Tomashenko, Xin Wang +7
The VoicePrivacy Challenge promotes the development of voice anonymisation solutions for speech technology. In this paper we present a systematic overview and analysis of the secon…
Revisiting and Improving Scoring Fusion for Spoofing-aware Speaker Verification Using Compositional Data Analysis
Xin Wang, Tomi Kinnunen, Kong Aik Lee +2
Fusing outputs from automatic speaker verification (ASV) and spoofing countermeasure (CM) is expected to make an integrated system robust to zero-effort imposters and synthesized s…
To what extent can ASV systems naturally defend against spoofing attacks?
Jee-weon Jung, Xin Wang, Nicholas Evans +6
The current automatic speaker verification (ASV) task involves making binary decisions on two types of trials: target and non-target. However, emerging advancements in speech gener…
The VoicePrivacy 2024 Challenge Evaluation Plan
Natalia Tomashenko, Xiaoxiao Miao, Pierre Champion +7
The task of the challenge is to develop a voice anonymization system for speech data which conceals the speaker's voice identity while protecting linguistic content and emotional s…
Can large-scale vocoded spoofed data improve speech spoofing countermeasure with a self-supervised front end?
Xin Wang, Junichi Yamagishi
A speech spoofing countermeasure (CM) that discriminates between unseen spoofed and bona fide data requires diverse training data. While many datasets use spoofed data generated by…
A comparison of recent waveform generation and acoustic modeling methods for neural-network-based speech synthesis
Xin Wang, Jaime Lorenzo-Trueba, Shinji Takaki +2
Recent advances in speech synthesis suggest that limitations such as the lossy nature of the amplitude spectrum with minimum phase approximation and the over-smoothing effect in ac…